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Kujdowicz M, Januś D, Taczanowska-Niemczuk A, Lankosz MW, Adamek D. Raman Spectroscopy as a Potential Adjunct of Thyroid Nodule Evaluation: A Systematic Review. Int J Mol Sci 2023; 24:15131. [PMID: 37894812 PMCID: PMC10607135 DOI: 10.3390/ijms242015131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/07/2023] [Accepted: 10/10/2023] [Indexed: 10/29/2023] Open
Abstract
The incidence of thyroid nodules (TNs) is estimated at 36.5% and 23% in females and males, respectively. A single thyroid nodule is usually detected during ultrasound assessment in patients with symptoms of thyroid dysfunction or neck mass. TNs are classified as benign tumours (non-malignant hyperplasia), benign neoplasms (e.g., adenoma, a non-invasive follicular tumour with papillary nuclear features) or malignant carcinomas (follicular cell-derived or C-cell derived). The differential diagnosis is based on fine-needle aspiration biopsies and cytological assessment (which is burdened with the bias of subjectivity). Raman spectroscopy (RS) is a laser-based, semiquantitative technique which shows for oscillations of many chemical groups in one label-free measurement. RS, through the assessment of chemical content, gives insight into tissue state which, in turn, allows for the differentiation of disease on the basis of spectral characteristics. The purpose of this study was to report if RS could be useful in the differential diagnosis of TN. The Web of Science, PubMed, and Scopus were searched from the beginning of the databases up to the end of June 2023. Two investigators independently screened key data using the terms "Raman spectroscopy" and "thyroid". From the 4046 records found initially, we identified 19 studies addressing the differential diagnosis of TNs applying the RS technique. The lasers used included 532, 633, 785, 830, and 1064 nm lines. The thyroid RS investigations were performed at the cellular and/or tissue level, as well as in serum samples. The accuracy of papillary thyroid carcinoma detection is approx. 90%. Furthermore, medullary, and follicular thyroid carcinoma can be detected with up to 100% accuracy. These results might be biased with low numbers of cases in some research and overfitting of models as well as the reference method. The main biochemical changes one can observe in malignancies are as follows: increase of protein, amino acids (like phenylalanine, tyrosine, and tryptophan), and nucleic acid content in comparison with non-malignant TNs. Herein, we present a review of the literature on the application of RS in the differential diagnosis of TNs. This technique seems to have powerful application potential in thyroid tumour diagnosis.
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Affiliation(s)
- Monika Kujdowicz
- Department of Pathomorphology, Faculty of Medicine, Jagiellonian University Medical College, Grzegorzecka 16, 31-531 Krakow, Poland;
- Department of Pathology, University Children Hospital in Krakow, 30-663 Krakow, Poland
| | - Dominika Januś
- Department of Pediatric and Adolescent Endocrinology, Institute of Pediatrics, Jagiellonian University Medical College, 31-531 Krakow, Poland;
- Department of Pediatric and Adolescent Endocrinology, University Children Hospital in Krakow, 30-663 Krakow, Poland
| | - Anna Taczanowska-Niemczuk
- Department of Pediatric Surgery, Institute of Pediatrics, Jagiellonian University Medical College, 31-531 Krakow, Poland;
- Department of Pediatric Surgery, University Children Hospital in Krakow, 30-663 Krakow, Poland
| | - Marek W. Lankosz
- Faculty of Physics and Applied Computer Science, AGH University of Krakow, Al. Mickiewicza 30, 30-059 Krakow, Poland;
| | - Dariusz Adamek
- Department of Pathomorphology, Faculty of Medicine, Jagiellonian University Medical College, Grzegorzecka 16, 31-531 Krakow, Poland;
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Bellantuono L, Tommasi R, Pantaleo E, Verri M, Amoroso N, Crucitti P, Di Gioacchino M, Longo F, Monaco A, Naciu AM, Palermo A, Taffon C, Tangaro S, Crescenzi A, Sodo A, Bellotti R. An eXplainable Artificial Intelligence analysis of Raman spectra for thyroid cancer diagnosis. Sci Rep 2023; 13:16590. [PMID: 37789191 PMCID: PMC10547772 DOI: 10.1038/s41598-023-43856-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 09/29/2023] [Indexed: 10/05/2023] Open
Abstract
Raman spectroscopy shows great potential as a diagnostic tool for thyroid cancer due to its ability to detect biochemical changes during cancer development. This technique is particularly valuable because it is non-invasive and label/dye-free. Compared to molecular tests, Raman spectroscopy analyses can more effectively discriminate malignant features, thus reducing unnecessary surgeries. However, one major hurdle to using Raman spectroscopy as a diagnostic tool is the identification of significant patterns and peaks. In this study, we propose a Machine Learning procedure to discriminate healthy/benign versus malignant nodules that produces interpretable results. We collect Raman spectra obtained from histological samples, select a set of peaks with a data-driven and label independent approach and train the algorithms with the relative prominence of the peaks in the selected set. The performance of the considered models, quantified by area under the Receiver Operating Characteristic curve, exceeds 0.9. To enhance the interpretability of the results, we employ eXplainable Artificial Intelligence and compute the contribution of each feature to the prediction of each sample.
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Affiliation(s)
- Loredana Bellantuono
- Dipartimento di Biomedicina Traslazionale e Neuroscienze (DiBraiN), Università degli Studi di Bari Aldo Moro, 70124, Bari, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125, Bari, Italy
| | - Raffaele Tommasi
- Dipartimento di Biomedicina Traslazionale e Neuroscienze (DiBraiN), Università degli Studi di Bari Aldo Moro, 70124, Bari, Italy
| | - Ester Pantaleo
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125, Bari, Italy
- Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, 70125, Bari, Italy
| | - Martina Verri
- Unit of Endocrine Organs and Neuromuscolar Pathology, Fondazione Policlinico Universitario Campus Bio-Medico, 00128, Rome, Italy
- Dipartimento di Scienze, Università degli Studi Roma Tre, 00146, Roma, Italy
| | - Nicola Amoroso
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125, Bari, Italy
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125, Bari, Italy
| | - Pierfilippo Crucitti
- Unit of Thoracic Surgery, Fondazione Policlinico Universitario Campus Bio-Medico, 00128, Rome, Italy
| | | | - Filippo Longo
- Unit of Thoracic Surgery, Fondazione Policlinico Universitario Campus Bio-Medico, 00128, Rome, Italy
| | - Alfonso Monaco
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125, Bari, Italy
- Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, 70125, Bari, Italy
| | - Anda Mihaela Naciu
- Unit of Metabolic Bone and Thyroid Diseases, Fondazione Policlinico Universitario Campus Bio-Medico, 00128, Rome, Italy
| | - Andrea Palermo
- Unit of Metabolic Bone and Thyroid Diseases, Fondazione Policlinico Universitario Campus Bio-Medico, 00128, Rome, Italy
| | - Chiara Taffon
- Unit of Endocrine Organs and Neuromuscolar Pathology, Fondazione Policlinico Universitario Campus Bio-Medico, 00128, Rome, Italy
| | - Sabina Tangaro
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125, Bari, Italy
- Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università degli Studi di Bari Aldo Moro, 70125, Bari, Italy
| | - Anna Crescenzi
- Unit of Endocrine Organs and Neuromuscolar Pathology, Fondazione Policlinico Universitario Campus Bio-Medico, 00128, Rome, Italy
| | - Armida Sodo
- Dipartimento di Scienze, Università degli Studi Roma Tre, 00146, Roma, Italy
| | - Roberto Bellotti
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125, Bari, Italy
- Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, 70125, Bari, Italy
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Sharma M, Li YC, Manjunatha SN, Tsai CL, Lin RM, Huang SF, Chang LB. Identification of Healthy Tissue from Malignant Tissue in Surgical Margin Using Raman Spectroscopy in Oral Cancer Surgeries. Biomedicines 2023; 11:1984. [PMID: 37509623 PMCID: PMC10377260 DOI: 10.3390/biomedicines11071984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 07/04/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
Accurate identification of tissue types in surgical margins is essential for ensuring the complete removal of cancerous cells and minimizing the risk of recurrence. The objective of this study was to explore the clinical utility of Raman spectroscopy for the detection of oral squamous cell carcinoma (OSCC) in both tumor and healthy tissues obtained from surgical resection specimens during surgery. This study enrolled a total of 64 patients diagnosed with OSCC. Among the participants, approximately 50% of the cases were classified as the most advanced stage, referred to as T4. Raman experiments were conducted on cryopreserved tissue samples collected from patients diagnosed with OSCC. Prominent spectral regions containing key oral biomarkers were analyzed using the partial least squares-support vector machine (PLS-SVM) method, which is a powerful multivariate analysis technique for discriminant analysis. This approach effectively differentiated OSCC tissue from non-OSCC tissue, achieving a sensitivity of 95.7% and a specificity of 93.3% with 94.7% accuracy. In the current study, Raman analysis of fresh tissue samples showed that OSCC tissues contained significantly higher levels of nucleic acids, proteins, and several amino acids compared to the adjacent healthy tissues. In addition to differentiating between OSCC and non-OSCC tissues, we have also explored the potential of Raman spectroscopy in classifying different stages of OSCC. Specifically, we have investigated the classification of T1, T2, T3, and T4 stages based on their Raman spectra. These findings emphasize the importance of considering both stage and subsite factors in the application of Raman spectroscopy for OSCC analysis. Future work will focus on expanding our tissue sample collection to better comprehend how different subsites influence the Raman spectra of OSCC at various stages, aiming to improve diagnostic accuracy and aid in identifying tumor-free margins during surgical interventions.
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Affiliation(s)
- Mukta Sharma
- Department of Electronic Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Ying-Chang Li
- Department of Ph.D. Program, Prospective Technology of Electrical Engineering and Computer Science, National Chin-Yi University of Technology, Taichung 411030, Taiwan
| | - S N Manjunatha
- Department of Electronic Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Chia-Lung Tsai
- Department of Electronic Engineering, Chang Gung University, Taoyuan 33302, Taiwan
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 333, Taiwan
| | - Ray-Ming Lin
- Department of Electronic Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Shiang-Fu Huang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 333, Taiwan
- Department of Public Health, Chang Gung University, Taoyuan 33302, Taiwan
| | - Liann-Be Chang
- Department of Electronic Engineering, Chang Gung University, Taoyuan 33302, Taiwan
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Palermo A, Sodo A, Naciu AM, Di Gioacchino M, Paolucci A, di Masi A, Maggi D, Crucitti P, Longo F, Perrella E, Taffon C, Verri M, Ricci MA, Crescenzi A. Clinical Use of Raman Spectroscopy Improves Diagnostic Accuracy for Indeterminate Thyroid Nodules. J Clin Endocrinol Metab 2022; 107:3309-3319. [PMID: 36103268 DOI: 10.1210/clinem/dgac537] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Indexed: 02/13/2023]
Abstract
BACKGROUND AND OBJECTIVE Molecular analysis of thyroid fine-needle aspiration (FNA) specimens is believed to improve the management of indeterminate nodules. Raman spectroscopy (RS) can differentiate benign and malignant thyroid lesions in surgically removed tissues, generating distinctive structural profiles. Herein, the diagnostic performance of RS was tested on FNA biopsies of thyroid gland. DESIGN Prospective, blinded, and single-center study. METHODS We enrolled 123 patients with indeterminate or more ominous cytologic diagnoses (TIR3A-low-risk indeterminate lesion, TIR3B-high-risk indeterminate lesion, TIR4-suspicious of malignancy, TIR5-malignant). All subjects were surgical candidates (defined by international guidelines) and submitted to FNA procedures for RS analysis. We compared RS data, cytologic findings, and final histologic assessments (as reference standard) using various statistical techniques. RESULTS The distribution of our study population was as follows: TIR3A:37, TIR3B:32, TIR4:16, and TIR5:38. In 30.9% of patients, histologic diagnoses were benign. For predicting thyroid malignancy in FNA samples, the overall specificity of RS was 86.8%, with 86.5% specificity in indeterminate cytologic categories. In patients with high-risk ultrasound categories, the specificity of RS increased to 87.5% for TIR3A, reaching 100% for TIR3B. Benign histologic diagnoses accounted for 72.9% of patients classified as TIR3A and 31.3% of those classified as TIR3B. Based on positive RS testing, unnecessary surgery was reduced to 7.4% overall (TIR3A-33.3%, TIR3B-6.7%). CONCLUSIONS This premier use of RS for thyroid cytology confirms its role as a valuable diagnostic tool and a valid alternative to molecular studies, capable of improving the management of indeterminate nodules and reducing unnecessary surgery.
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Affiliation(s)
- Andrea Palermo
- Unit of Metabolic Bone and Thyroid Disorders, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200 - 00128 Roma, Italy
- Unit of Endocrinology and Diabetes, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21 - 00128 Roma, Italy
| | - Armida Sodo
- Dipartimento di Scienze, Università Roma Tre, Rome, Italy
| | - Anda Mihaela Naciu
- Unit of Metabolic Bone and Thyroid Disorders, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200 - 00128 Roma, Italy
| | | | | | | | - Daria Maggi
- Unit of Endocrinology and Diabetes, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy
| | - Pierfilippo Crucitti
- Unit of Thoracic Surgery, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy
| | - Filippo Longo
- Unit of Thoracic Surgery, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy
| | - Eleonora Perrella
- Unit of Pathology, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy
| | - Chiara Taffon
- Unit of Pathology, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy
| | - Martina Verri
- Unit of Pathology, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy
| | | | - Anna Crescenzi
- Unit of Pathology, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy
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5
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A Comparison of PCA-LDA and PLS-DA Techniques for Classification of Vibrational Spectra. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12115345] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Vibrational spectroscopies provide information about the biochemical and structural environment of molecular functional groups inside samples. Over the past few decades, Raman and infrared-absorption-based techniques have been extensively used to investigate biological materials under different pathological conditions. Interesting results have been obtained, so these techniques have been proposed for use in a clinical setting for diagnostic purposes, as complementary tools to conventional cytological and histological techniques. In most cases, the differences between vibrational spectra measured for healthy and diseased samples are small, even if these small differences could contain useful information to be used in the diagnostic field. Therefore, the interpretation of the results requires the use of analysis techniques able to highlight the minimal spectral variations that characterize a dataset of measurements acquired on healthy samples from a dataset of measurements relating to samples in which a pathology occurs. Multivariate analysis techniques, which can handle large datasets and explore spectral information simultaneously, are suitable for this purpose. In the present study, two multivariate statistical techniques, principal component analysis-linear discriminate analysis (PCA-LDA) and partial least square-discriminant analysis (PLS-DA) were used to analyse three different datasets of vibrational spectra, each one including spectra of two different classes: (i) a simulated dataset comprising control-like and exposed-like spectra, (ii) a dataset of Raman spectra measured for control and proton beam-exposed MCF10A breast cells and (iii) a dataset of FTIR spectra measured for malignant non-metastatic MCF7 and metastatic MDA-MB-231 breast cancer cells. Both PCA-LDA and PLS-DA techniques were first used to build a discrimination model by using calibration sets of spectra extracted from the three datasets. Then, the classification performance was established by using test sets of unknown spectra. The achieved results point out that the built classification models were able to distinguish the different spectra types with accuracy between 93% and 100%, sensitivity between 86% and 100% and specificity between 90% and 100%. The present study confirms that vibrational spectroscopy combined with multivariate analysis techniques has considerable potential for establishing reliable diagnostic models.
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6
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Wendler T, van Leeuwen FWB, Navab N, van Oosterom MN. How molecular imaging will enable robotic precision surgery : The role of artificial intelligence, augmented reality, and navigation. Eur J Nucl Med Mol Imaging 2021; 48:4201-4224. [PMID: 34185136 PMCID: PMC8566413 DOI: 10.1007/s00259-021-05445-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 06/01/2021] [Indexed: 02/08/2023]
Abstract
Molecular imaging is one of the pillars of precision surgery. Its applications range from early diagnostics to therapy planning, execution, and the accurate assessment of outcomes. In particular, molecular imaging solutions are in high demand in minimally invasive surgical strategies, such as the substantially increasing field of robotic surgery. This review aims at connecting the molecular imaging and nuclear medicine community to the rapidly expanding armory of surgical medical devices. Such devices entail technologies ranging from artificial intelligence and computer-aided visualization technologies (software) to innovative molecular imaging modalities and surgical navigation (hardware). We discuss technologies based on their role at different steps of the surgical workflow, i.e., from surgical decision and planning, over to target localization and excision guidance, all the way to (back table) surgical verification. This provides a glimpse of how innovations from the technology fields can realize an exciting future for the molecular imaging and surgery communities.
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Affiliation(s)
- Thomas Wendler
- Chair for Computer Aided Medical Procedures and Augmented Reality, Technische Universität München, Boltzmannstr. 3, 85748 Garching bei München, Germany
| | - Fijs W. B. van Leeuwen
- Department of Radiology, Interventional Molecular Imaging Laboratory, Leiden University Medical Center, Leiden, The Netherlands
- Department of Urology, The Netherlands Cancer Institute - Antonie van Leeuwenhoek Hospital, Amsterdam, The Netherlands
- Orsi Academy, Melle, Belgium
| | - Nassir Navab
- Chair for Computer Aided Medical Procedures and Augmented Reality, Technische Universität München, Boltzmannstr. 3, 85748 Garching bei München, Germany
- Chair for Computer Aided Medical Procedures Laboratory for Computational Sensing + Robotics, Johns-Hopkins University, Baltimore, MD USA
| | - Matthias N. van Oosterom
- Department of Radiology, Interventional Molecular Imaging Laboratory, Leiden University Medical Center, Leiden, The Netherlands
- Department of Urology, The Netherlands Cancer Institute - Antonie van Leeuwenhoek Hospital, Amsterdam, The Netherlands
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7
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Sharma M, Jeng MJ, Young CK, Huang SF, Chang LB. Developing an Algorithm for Discriminating Oral Cancerous and Normal Tissues Using Raman Spectroscopy. J Pers Med 2021; 11:jpm11111165. [PMID: 34834517 PMCID: PMC8623962 DOI: 10.3390/jpm11111165] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 11/01/2021] [Accepted: 11/08/2021] [Indexed: 11/17/2022] Open
Abstract
The aim of this study was to investigate the clinical potential of Raman spectroscopy (RS) in detecting oral squamous cell carcinoma (OSCC) in tumor and healthy tissues in surgical resection specimens during surgery. Raman experiments were performed on cryopreserved specimens from patients with OSCC. Univariate and multivariate analysis was performed based on the fingerprint region (700–1800 cm−1) of the Raman spectra. One hundred thirty-one ex-vivo Raman experiments were performed on 131 surgical resection specimens obtained from 67 patients. The principal component analysis (PCA) and partial least square (PLS) methods with linear discriminant analysis (LDA) were applied on an independent validation dataset. Both models were able to differentiate between the tissue types, but PLS–LDA showed 100% accuracy, sensitivity, and specificity. In this study, Raman measurements of fresh resection tissue specimens demonstrated that OSCC had significantly higher nucleic acid, protein, and several amino acid contents than adjacent healthy tissues. The specific spectral information obtained in this study can be used to develop an in vivo Raman spectroscopic method for the tumor-free resection boundary during surgery.
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Affiliation(s)
- Mukta Sharma
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan; (M.S.); (L.-B.C.)
| | - Ming-Jer Jeng
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan; (M.S.); (L.-B.C.)
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan;
- Correspondence:
| | - Chi-Kuang Young
- Department of Otolaryngology, Head and Neck Surgery, Chang Gung Memorial Hospital, Keelung Branch, Keelung 204, Taiwan;
| | - Shiang-Fu Huang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan;
- Department of Public Health, Chang Gung University, Taoyuan 333, Taiwan
| | - Liann-Be Chang
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan; (M.S.); (L.-B.C.)
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan;
- Green Technology Research Center, Chang Gung University, Taoyuan 333, Taiwan
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Identifying benign and malignant thyroid nodules based on blood serum surface-enhanced Raman spectroscopy. NANOMEDICINE-NANOTECHNOLOGY BIOLOGY AND MEDICINE 2020; 32:102328. [PMID: 33181274 DOI: 10.1016/j.nano.2020.102328] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 10/15/2020] [Accepted: 10/22/2020] [Indexed: 02/06/2023]
Abstract
The aim of this study is to evaluate the feasibility of using blood serum surface-enhanced Raman spectroscopy (SERS) to identify benign and malignant thyroid nodules. Blood serum samples collected from three different groups including healthy volunteers (n = 22), patients with benign nodules (n = 19) and malignant nodules (n = 22) were measured by SERS. The spectral analysis results demonstrate that biomolecules in serum, such as amino acids, adenine and nucleic acid bases, change differently due to the different progression of nodules. By further combining with partial least square analysis and linear discriminant analysis (PLS-LDA) method, diagnostic accuracies of 93.65% and 82.93%, sensitivities of 92.68% and 81.82% and specificities of 95.45% and 84.21% can be achieved for differentiating healthy versus thyroid nodular groups and benign versus malignant groups, respectively. The above results have suggested that the blood serum SERS technique is helpful for precise diagnosis and timely treatment for patients with thyroid nodules.
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9
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Bueno JM, Ávila FJ, Hristu R, Stanciu SG, Eftimie L, Stanciu GA. Objective analysis of collagen organization in thyroid nodule capsules using second harmonic generation microscopy images and the Hough transform. APPLIED OPTICS 2020; 59:6925-6931. [PMID: 32788782 DOI: 10.1364/ao.393721] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 06/29/2020] [Indexed: 06/11/2023]
Abstract
Papillary carcinoma is the most prevalent type of thyroid cancer. Its diagnosis requires accurate and subjective analyses from expert pathologists. Here we propose a method based on the Hough transform (HT) to detect and objectively quantify local structural differences in collagen thyroid nodule capsules. Second harmonic generation (SHG) microscopy images were acquired on non-stained histological sections of capsule fragments surrounding the healthy thyroid gland and benign and tumoral/malignant nodules. The HT was applied to each SHG image to extract numerical information on the organization of the collagen architecture in the tissues under analysis. Results show that control thyroid capsule samples present a non-organized structure composed of wavy collagen distribution with local orientations. On the opposite, in capsules surrounding malignant nodules, a remodeling of the collagen network takes place and local undulations disappear, resulting in an aligned pattern with a global preferential orientation. The HT procedure was able to quantitatively differentiate thyroid capsules from capsules surrounding papillary thyroid carcinoma (PTC) nodules. Moreover, the algorithm also reveals that the collagen arrangement of the capsules surrounding benign nodules significantly differs from both the thyroid control and PTC nodule capsules. Combining SHG imaging with the HT results thus in an automatic and objective tool to discriminate between the pathological modifications that affect the capsules of thyroid nodules across the progressions of PTC, with potential to be used in clinical settings to complement current state-of-the-art diagnostic methods.
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10
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Abstract
Over the last 50 years, the incidence of human thyroid cancer disease has seen a significative increment. This comes along with an even higher increment of surgery, since, according to the international guidelines, patients are sometimes addressed to surgery also when the fine needle aspiration gives undetermined cytological diagnosis. As a matter of fact, only 30% of the thyroid glands removed for diagnostic purpose have a post surgical histological report of malignancy: this implies that about 70% of the patients have suffered an unnecessary thyroid removal. Here we show that Raman spectroscopy investigation of thyroid tissues provides reliable cancer diagnosis. Healthy tissues are consistently distinguished from cancerous ones with an accuracy of \documentclass[12pt]{minimal}
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\begin{document}$$\sim $$\end{document}∼ 90%, and the three cancer typology with highest incidence are clearly identified. More importantly, Raman investigation has evidenced alterations suggesting an early stage of transition of adenoma tissues into cancerous ones. These results suggest that Raman spectroscopy may overcome the limits of current diagnostic tools.
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11
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Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection. Cancers (Basel) 2020; 12:cancers12020373. [PMID: 32041119 PMCID: PMC7072687 DOI: 10.3390/cancers12020373] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 02/03/2020] [Accepted: 02/04/2020] [Indexed: 12/17/2022] Open
Abstract
Physicians use sonographic characteristics as a reference for the possible diagnosis of thyroid cancers. The purpose of this study was to investigate whether physicians were more effective in their tentative diagnosis based on the information provided by a computer-aided detection (CAD) system. A computer compared software-defined and physician-adjusted tumor loci. A multicenter, multireader, and multicase (MRMC) study was designed to compare clinician performance without and with the use of CAD. Interobserver variability was also analyzed. Excellent, satisfactory, and poor segmentations were observed in 25.3%, 58.9%, and 15.8% of nodules, respectively. There were 200 patients with 265 nodules in the study set. Nineteen physicians scored the malignancy potential of the nodules. The average area under the curve (AUC) of all readers was 0.728 without CAD and significantly increased to 0.792 with CAD. The average standard deviation of the malignant potential score significantly decreased from 18.97 to 16.29. The mean malignant potential score significantly decreased from 35.01 to 31.24 for benign cases. With the CAD system, an additional 7.6% of malignant nodules would be suggested for further evaluation, and biopsy would not be recommended for an additional 10.8% of benign nodules. The results demonstrated that applying a CAD system would improve clinicians’ interpretations and lessen the variability in diagnosis. However, more studies are needed to explore the use of the CAD system in an actual ultrasound diagnostic situation where much more benign thyroid nodules would be seen.
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12
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Dang TT, Feyissa AH, Gringer N, Jessen F, Olsen K, Bøknæs N, Orlien V. Effects of high pressure and ohmic heating on shell loosening, thermal and structural properties of shrimp (Pandalus borealis). INNOV FOOD SCI EMERG 2020. [DOI: 10.1016/j.ifset.2019.102246] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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de Oliveira MAS, Campbell M, Afify AM, Huang EC, Chan JW. Hyperspectral Raman microscopy can accurately differentiate single cells of different human thyroid nodules. BIOMEDICAL OPTICS EXPRESS 2019; 10:4411-4421. [PMID: 31565498 PMCID: PMC6757446 DOI: 10.1364/boe.10.004411] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 06/24/2019] [Accepted: 07/08/2019] [Indexed: 05/07/2023]
Abstract
We report on the use of line-scan hyperspectral Raman microscopy in combination with multivariate statistical analyses for identifying and classifying single cells isolated from clinical samples of human thyroid nodules based on their intrinsic Raman spectral signatures. A total of 248 hyperspectral Raman images of single cells from benign thyroid (n = 127) and classic variant of papillary carcinoma (n = 121) nodules were collected. Spectral differences attributed to phenylalanine, tryptophan, proteins, lipids, and nucleic acids were identified for benign and papillary carcinoma cells. Using principal component analysis and linear discriminant analysis, cells were identified with 97% diagnostic accuracy. In addition, preliminary data of cells from follicular adenoma (n = 20), follicular carcinoma (n = 25), and follicular variant of papillary carcinoma (n = 18) nodules suggest the feasibility of further discrimination of subtypes. Our findings indicate that hyperspectral Raman microscopy can potentially be developed into an objective approach for analyzing single cells from fine needle aspiration (FNA) biopsies to enable the minimally invasive diagnosis of "indeterminate" thyroid nodules and other challenging cases.
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Affiliation(s)
- Marcos A. S. de Oliveira
- Department of Pathology & Laboratory Medicine, Univ. of California Davis, Sacramento, CA 95817, USA
| | - Michael Campbell
- Department of Surgery, Univ. of California Davis, Sacramento, CA 95817, USA
| | - Alaa M. Afify
- Department of Pathology & Laboratory Medicine, Univ. of California Davis, Sacramento, CA 95817, USA
| | - Eric C. Huang
- Department of Pathology, Univ. of Washington, Seattle, WA 98104, USA
- ECH and JWC contributed equally as senior authors
| | - James W. Chan
- Department of Pathology & Laboratory Medicine, Univ. of California Davis, Sacramento, CA 95817, USA
- ECH and JWC contributed equally as senior authors
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14
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Taylor JN, Mochizuki K, Hashimoto K, Kumamoto Y, Harada Y, Fujita K, Komatsuzaki T. High-Resolution Raman Microscopic Detection of Follicular Thyroid Cancer Cells with Unsupervised Machine Learning. J Phys Chem B 2019; 123:4358-4372. [PMID: 31035762 DOI: 10.1021/acs.jpcb.9b01159] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
We use Raman microscopic images with high spatial and spectral resolution to investigate differences between human follicular thyroid (Nthy-ori 3-1) and follicular thyroid carcinoma (FTC-133) cells, a well-differentiated thyroid cancer. Through comparison to classification of single-cell Raman spectra, the importance of subcellular information in the Raman images is emphasized. Subcellular information is extracted through a coarse-graining of the spectra at high spatial resolution (∼1.7 μm2), producing a set of characteristic spectral groups representing locations having similar biochemical compositions. We develop a cell classifier based on the frequencies at which the characteristic spectra appear within each of the single cells. Using this classifier, we obtain a more accurate (89.8%) distinction of FTC-133 and Nthy-ori 3-1, in comparison to single-cell spectra (77.6%). We also infer which subcellular components are important to cellular distinction; we find that cancerous FTC-133 cells contain increased populations of lipid-containing components and decreased populations of cytochrome-containing components relative to Nthy-ori 3-1, and that the regions containing these contributions are largely outside the cell nuclei. In addition to increased classification accuracy, this approach provides rich subcellular information about biochemical differences and cellular locations associated with the distinction of the normal and cancerous follicular thyroid cells.
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Affiliation(s)
- J Nicholas Taylor
- Research Institute for Electronic Science , Hokkaido University , Kita 20, Nishi 10 , Kita-ku, Sapporo 001-0020 , Japan
| | - Kentaro Mochizuki
- Department of Applied Physics , Osaka University , 2-1 Yamadaoka , Suita, Osaka 565-0871 , Japan
| | - Kosuke Hashimoto
- Department of Pathology and Cell Regulation, Graduate School of Medical Science , Kyoto Prefectural University of Medicine , Kajii-cho, Kawaramachi-Hirokoji, Kyoto , 602-8566 , Japan
| | - Yasuaki Kumamoto
- Department of Pathology and Cell Regulation, Graduate School of Medical Science , Kyoto Prefectural University of Medicine , Kajii-cho, Kawaramachi-Hirokoji, Kyoto , 602-8566 , Japan
| | - Yoshinori Harada
- Department of Pathology and Cell Regulation, Graduate School of Medical Science , Kyoto Prefectural University of Medicine , Kajii-cho, Kawaramachi-Hirokoji, Kyoto , 602-8566 , Japan
| | - Katsumasa Fujita
- Department of Applied Physics , Osaka University , 2-1 Yamadaoka , Suita, Osaka 565-0871 , Japan.,Advanced Photonics and Biosensing Open Innovation Laboratory , AIST-Osaka University , Yamadaoka , Suita, Osaka 565-0871 , Japan.,Transdimensional Life Imaging Division, Institute for Open and Transdisciplinary Research Initiatives , Osaka University , Yamadaoka , Suita, Osaka 565-0871 , Japan
| | - Tamiki Komatsuzaki
- Research Institute for Electronic Science , Hokkaido University , Kita 20, Nishi 10 , Kita-ku, Sapporo 001-0020 , Japan.,Institute for Chemical Reaction Design and Discovery (WPI-ICReDD) , Hokkaido University , Kita 21 Nishi 10 , Kita-ku, Sapporo , Hokkaido 001-0021 , Japan.,Laboratoire Interdisciplinaire Carnot de Bourgogne , UMR 6303 CNRS-Université Bourgogne Franche-Comt , 9 Avenue A. Savary, BP 47 870 , F-21078 , Dijon Cedex , France
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15
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Depciuch J, Stanek-Widera A, Skrzypiec D, Lange D, Biskup-Frużyńska M, Kiper K, Stanek-Tarkowska J, Kula M, Cebulski J. Spectroscopic identification of benign (follicular adenoma) and cancerous lesions (follicular thyroid carcinoma) in thyroid tissues. J Pharm Biomed Anal 2019; 170:321-326. [PMID: 30954022 DOI: 10.1016/j.jpba.2019.03.061] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 03/25/2019] [Accepted: 03/27/2019] [Indexed: 01/03/2023]
Abstract
Thyroid follicular nodules are quite common in the population, however only a small proportion is malignant. Thyroid cancer differs from adenoma by features of cellular atypia, angioinvasiveness and possibility of metastasis via blood vessels mainly in the lungs and bones. Pathomorphological examination of the postoperative material plays a significant role in the diagnosis of cystic thyroid lesions. De facto, there is no possibility to determine with certainty whether the lesion is benign or malignant before surgery, therefore new methods are being sought to meet clinical needs. The study aimed to investigate if Fourier-transform infrared spectroscopy (FTIR) spectroscopy and Raman spectroscopy combined with multidimensional analysis can be a useful tool in distinguishing between thyroid adenomas and carcinomas. The obtained results indicate quantitative and qualitative alterations within proteins and fats derived from patients' tissues samples. Raman spectroscopy additionally shows significant changes in the amount of tissue collagen due to the pathogenic process. In the spectra of the second FTIR derivative, shifts of vibrations corresponding to the β-sheet and α-helix structure are observed towards the lower rates of wave numbers in the case of neoplastic tissues. Using the leave-one-out cross-validation, sensitivity and specificity calculated with Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA) clearly shows the possibility to distinguish between pathologically changed and normal thyroid tissue as well as differentiate follicular thyroid adenoma (FTA) from widely invasive follicular thyroid carcinoma (WI-FTC) tissues.
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Affiliation(s)
- Joanna Depciuch
- Institute of Nuclear Physics Polish Academy of Sciences, PL-31342, Krakow, Poland.
| | - Agata Stanek-Widera
- Department of Tumor Pathology, Maria Sklodowska-Curie Memorial Cancer Centre and Institute of Oncology, PL-44101, Gliwice, Poland
| | - Dominika Skrzypiec
- Center for Innovation and Transfer of Natural Sciences and Engineering Knowledge, University of Rzeszow, PL-35959, Rzeszow, Poland
| | - Dariusz Lange
- Department of Tumor Pathology, Maria Sklodowska-Curie Memorial Cancer Centre and Institute of Oncology, PL-44101, Gliwice, Poland
| | - Magdalena Biskup-Frużyńska
- Department of Tumor Pathology, Maria Sklodowska-Curie Memorial Cancer Centre and Institute of Oncology, PL-44101, Gliwice, Poland
| | - Krzysztof Kiper
- Faculty of Medicine, University of Rzeszow, PL-35959, Rzeszow, Poland
| | | | - Monika Kula
- Polish Academy of Sciences, The Franciszek Górski Institute of Plant Physiology, Niezapominajek 21, 30239, Krakow, Poland
| | - Jozef Cebulski
- Center for Innovation and Transfer of Natural Sciences and Engineering Knowledge, University of Rzeszow, PL-35959, Rzeszow, Poland
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16
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Raman spectroscopy discriminates malignant follicular lymphoma from benign follicular hyperplasia and from tumour metastasis. Talanta 2018; 194:763-770. [PMID: 30609603 DOI: 10.1016/j.talanta.2018.10.086] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 10/24/2018] [Accepted: 10/26/2018] [Indexed: 02/08/2023]
Abstract
Raman spectroscopy is a non-destructive label-free technique providing biochemical tissue fingerprint. The objective of the present work was to test if Raman spectroscopy is a suitable tool to differentiate lymph nodes affected by different conditions, such as reactive follicular hyperplasia (benign), follicular lymphoma (low grade primary tumour), diffuse large B cell lymphoma (high grade primary tumour) and tumour metastasis (secondary tumours). Moreover, we tested its ability to discriminate follicular lymphomas by the tumour grade and the BCL2 protein expression. Lymph nodes collected from 20 patients, who underwent surgery for suspected malignancy, were investigated. Imaging of tissue areas from about 400 µm2 up to 2 mm2 was performed collecting Raman maps containing thousands of spectra. Partial least squares discriminant analysis (PLS-DA) - a bilinear classification method - was used to calculate lymph node classification models, in order to discriminate at first between benign and malignant tissues and successively among cancer types, grades and the BCL2 protein expression. This proof-of-concept study paves the way for the development of clinical optical biopsy tools for lymph node cancer diagnosis, complementary to histopathological assessment.
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17
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O'Dea D, Bongiovanni M, Sykiotis GP, Ziros PG, Meade AD, Lyng FM, Malkin A. Raman spectroscopy for the preoperative diagnosis of thyroid cancer and its subtypes: An in vitro proof-of-concept study. Cytopathology 2018; 30:51-60. [DOI: 10.1111/cyt.12636] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Revised: 06/29/2018] [Indexed: 12/14/2022]
Affiliation(s)
- Declan O'Dea
- School of Biological Sciences; Dublin Institute of Technology; Dublin Ireland
- DIT Centre for Radiation and Environment Science; Focas Research Institute; Dublin Institute of Technology; Dublin Ireland
| | | | - Gerasimos P. Sykiotis
- Service of Endocrinology, Diabetology and Metabolism; Lausanne University Hospital; Lausanne Switzerland
| | - Panos G. Ziros
- Service of Endocrinology, Diabetology and Metabolism; Lausanne University Hospital; Lausanne Switzerland
| | - Aidan D. Meade
- DIT Centre for Radiation and Environment Science; Focas Research Institute; Dublin Institute of Technology; Dublin Ireland
- School of Physics & Clinical & Optometric Sciences; Dublin Institute of Technology; Dublin Ireland
| | - Fiona M. Lyng
- DIT Centre for Radiation and Environment Science; Focas Research Institute; Dublin Institute of Technology; Dublin Ireland
- School of Physics & Clinical & Optometric Sciences; Dublin Institute of Technology; Dublin Ireland
| | - Alison Malkin
- School of Biological Sciences; Dublin Institute of Technology; Dublin Ireland
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